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Utilizing Machine Learning For Respiratory Rate Detection Via Radar Sensor
Elhadad, Anwar
Elhadad, Anwar
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Abstract
In this research, we investigate a data processing method to capture the respiratory rate of a person by utilizing a doppler radar to monitor their body movement during respiration. We utilize a machine learning algorithm with a radar sensor to capture the chest movement of a person while breathing and determine the respiratory rate according to that movement. We are using a Random Forest classifier to distinguish between different classes of pulses. After that, the algorithm constructs a sinusoidal signal representing the breathing rate of the sample. By applying this technique, we can detect the breathing rate accurately for different subjects by analyzing the evolution of the reflected pulse while breathing. Furthermore, we can detect the change in pulse width ratio between the pulses of the classes across multiple breaths
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Date
2020-01-01